Macroecology of infectious disease and networked populations

What is macroecology?

What is macroecology?

How do we do it?

  • Large observational data

  • Some theory, but not much currently

  • Makes it tough to get at mechanism

  • …but maybe that’s not the point

What do parasites have to do with macroecology?

  • Parasites can provide good tests of macroecological ideas

An example:

  • Some macreocological ideas claim that metabolic constraints on thermoregulation determine the distribution of diversity. Ectotherms (like parasites) could provide a good test of this specific hypothesis

I pitched this in 2011!!

What’s the scope of parasite macroecology we’ll cover

  • the standard flavors (ldr, range size stuff, parasite body size scaling, etc. )

  • host-parasite networks ( the next frontier!)

first we need some data

London Natural History Museum Host-Helminth data

  • 299 geopolitical locations

  • 23601 parasite species

  • 14933 host species

  • 94561 interactions

London Natural History Museum Host-Helminth data

others exist, like VIRION, GMPD2.0, etc.

Recall this figure of parasite taxonomic diversity?

Latitudinal diversity gradient

tendency for species richness to be highest near the equator and lowest near the poles

Think-pair share (3 minutes): How many of the putative mechanisms underlying this pattern can we come up?

Latitudinal diversity gradient

Latitudinal diversity gradient (but with parasites)

Another potential mechanism

The mid-domain effect

  • Interesting because it is essentially a null model

  • Ignores all species differences and generates the relationship

Bergmann’s rule

tendency for species body size to be larger away from equator

Main proposed mechanism is larger body mass increases surface-to-volume ratio, important for heat retention.

  • Do we expect parasites to follow Bergmann’s rule?

  • Can be examined across species or within a single species!

Bergmann’s rule

Bergmann’s rule

Is this support?

What’s going on with temperature in the right panels?

Harrison’s rule

Large parasites should only infect large host species

This is a modified Harrison’s rule from Poulin (how?)

Island biogeography theory

Island biogeography theory (but with parasites)

Island biogeography theory (but with parasites)

Distance decay relationships

  • Island biogeography is supposed to give us equilibrial species richness

  • But macroecology can also relate to species composition

Increasing geographic distance should result in more dissimilar communities

Distance decay relationships

What if all these patterns are just driven by host richness?

Totally possible. Parasites are simply tracking their hosts, and their showing macroecological patterns is simply a function of the host community

Ways around this

  • standardize parasite diversity by host diversity

  • compare strength of macroecological relationships between host and parasite communities

  • give up (jk)

The macroecology of species interaction networks

We’ve seen networks before

The macroecology of species interaction networks

We’ve seen networks before

The macroecology of species interaction networks

We’ve seen networks before

The macroecology of species interaction networks

We’ve seen networks before

The macroecology of species interaction networks



That’s because networks are awesome!




End of lecture 1

What have we learned

  • There are many ways to study host-parasite interactions

  • Macroecology is one way, which looks at large spatial/taxonomic/temporal patterns

  • Ignores a lot of detail and specifics of host-parasite interactions

  • But is still neato

  • Now let’s talk about networks

Why networks?

  • They are also neato

  • They relate to concepts we’ve already covered (specificity, host range, parasite species richness, etc. etc.)

  • Host-parasite interactions do not exist in isolation (we saw that!)

Unipartite networks

  • consist of one class of interactor and the links between them

    • transportation networks
    • social networks
    • sexual contact networks
    • etc.

Bipartite networks

  • consist of two classes of interactors

    • actor-movie
    • artist-listener
    • plant-pollinator
    • host-parasite

The web of interactions between small mammals and their parasites in New Mexico

What can we measure about these networks?

Centrality

  • degree : sum of links for a given interactor

  • closeness : weighted distance between interactors

  • betweenness : weighted by shortest paths that pass through an interactor

What does each of these correspond to in a host-parasite network? (5 minute paired discussion)

What can we measure about these networks?

  • Nestedness : tendency of interactions to form into nested subsets

Have we seen concepts like this before? What does this start to get at?

The macroecology of host-parasite networks

  • A lot of this is beyond the course, so we won’t really cover it.

  • The core goal is to leverage macroecological ideas into thinking about how host-parasite networks change across spatial and environmental gradients

And folks have been thinking about this!

But what if we simplify our approach to just considering social networks (unipartite)?

Disease spread in networked populations

We saw this in the sexual contact network lecture!

But we didn’t talk about mitigation

Who would you vaccinate in this network?

Removing a single well-connected individual

Removing the top interactors (compared to random, based on degree)

Removing the top interactors (compared to random, based on closeness)

That was fun, right!?

  • The structure of the network really matters when considering control options

  • This is why targeted vaccination campaigns work!

  • We don’t ‘ring cull’ people, right?

But what if we simplify our approach to just considering spatial networks?